神经网络7种C语言实现代码，大家可以

遗传优化神经网络结构，C++源代码-Genetic optimization of neural network architecture, C++ Source code

使用pca和svm方法对表情进行分类，有较高的识别准确率。

人工智能实验 -experimental AI Artificial Intelligence Experiment

模拟退火算法 模拟退火算法(Simulated Annealing,简称SA算法)是模拟加热熔化的金属的退火过程，来寻找全局最优解的有效方法之一。 模拟退火的基本思想和步骤如下： 设S＝{s1,s2,…,sn}为所有可能的状态所构成的集合， f：S―R为非负代价函数，即优化问题抽象如下： 寻找s*∈S，使得f(s*)＝min f(si) 任意si∈S （1）给定一较高初始温度T，随机产生初始状态S （2）按一定方式，对当前状态作随机扰动，产生一个新的状态S’ S’＝S＋sign(η).δ 其中δ为给定的步长， η为[－1,1]的随机数-simulated annealing algorithm (Simulated Annealing, or SA algorithm) is a simulation of heating molten metal in the annealing process, to find the global optimum one of the effective ways. Simulated Annealing basic ideas and the steps are as follows : S = (s1, s2, ..., sn) for all possible state posed by the pool, f : S-R non-negative cost function, that is abstract optimization problems are as follows : Find S* s, making f (s*) = min f (si) arbitrary si S (1) to set a higher initial temperature T, randomly generated initial state S (2) of a certain form, the current state of random disturbance, have a new state S "S" = S+ sign (). delta where given for the step, [-1,1] Random Number

模拟退火算法求解经典图论中的图着色问题的源程序-simulated annealing algorithm classic graph coloring map of the source

人工智能经典问题TSP问题的C语言实现，内含源程序和调试过程生成的文件-AI classic TSP"s C language, and includes source code debugging process produces files

一个高人的VC实现NN的程序。很不错。先运行Matrixbase.dsw,again arithmetic.dsw, next nnbp.dsw,final neuralNetWork.dsw.-an expert in VC NN procedures. Very good. First running Matrixbase.dsw, again arithmetic.dsw. next nnbp.dsw, final neuralNetWork.dsw.

机器人编程方法，主要是讲c的， 期刊论文-Robot programming method, mainly stresses c and Journal Papers

Libsvm is a simple, easy-to-use, and efficient software for SVM classification and regression. It solves C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM regression, and nu-SVM regression. It also provides an automatic model selection tool for C-SVM classification. This document explains the use of libsvm.

一个遗传算法C++类,值得收藏！-a genetic algorithm C-worthy collection!